[R] glm help - final predictor variable NA

[Rolf Turner]

Psigh!  Why do people think that it is perfectly OK to undertake 
statistical analyses without knowing or understanding any statistics?
(I guess it's slightly less dangerous than undertaking to do your own 
wiring without knowing anything about being an electrician, but still ....)

However, to stop venting and answer your question:  It is because 
"CDSTotal" is perfectly confounded (in the given design) with the other 
predictors. That is, CDSTotal is exactly equal to a linear combination 
of the other predictors (and the constant "1").

Try:

lm(CDSTotal ~ Age + Gender + LOC + PC + Stability, data=Controlgroup)

and you will find that the error sum of squares is zero (to within 
numerical tolerance).

cheers,

Rolf Turner

-- 
Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276

On 22/07/15 06:56, matthewjones43 wrote:

> Hi, I am not a statistician and so I am sure whatever it is I am doing wrong
> must be an obvious error for those who are...Basically I can not understand
> why I get NA for variable 'CDSTotal' when running a glm? Does anyone have an
> idea of why this might be happening?
>
> Call:  glm(formula = cbind(SRAS - 26, 182 - SRAS) ~ Age + Gender + LOC +
>      PC + Stability + CDSTotal, family = binomial, data = Controlgroup)
>
> Coefficients:
> (Intercept)          Age       Gender          LOC           PC    Stability
>    -2.575071     0.009148     0.354143     0.018295    -0.011317     0.090759
>     CDSTotal
>           NA
>
> Degrees of Freedom: 64 Total (i.e. Null);  59 Residual
> Null Deviance:	    2015
> Residual Deviance: 1264 	AIC: 1614